Fast algorithms for nonparametric population modeling of large data sets

Population models are widely applied in biomedical data analysis since they characterize both the average and individual responses of a population of subjects. In the absence of a reliable mechanistic model, one can resort to the Bayesian nonparametric approach that models the individual curves as G...

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Vydáno v:	Automatica (Oxford) Ročník 45; číslo 1; s. 173 - 179
Hlavní autoři:	Pillonetto, Gianluigi, De Nicolao, Giuseppe, Chierici, Marco, Cobelli, Claudio
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 2009 Elsevier
Témata:	Applied sciences Bayesian estimation Computer science; control theory; systems Control theory. Systems Estimation theory Exact sciences and technology Gaussian processes Glucose metabolism Nonparametric identification Glucose metabolism Bayesian estimation Nonparametric identification Gaussian processes Estimation theory Bayes estimation Data analysis Non parametric estimation Data processing Client server architecture Metabolism Modeling Gaussian process System identification Fast algorithm Sampling Biomedical engineering
ISSN:	0005-1098, 1873-2836
On-line přístup:	Získat plný text
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